# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
# Copyright 2021 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import numpy as np
from tensorflow.python.ops import init_ops

from core.leras import nn

tf = nn.tf

from .CA import CAInitializerSubprocessor

class initializers():
    class ca (init_ops.Initializer):
        def __call__(self, shape, dtype=None, partition_info=None):
            return tf.zeros( shape, dtype=dtype, name="_cai_")

        @staticmethod
        def generate_batch( data_list, eps_std=0.05 ):
            # list of (shape, np.dtype)
            return CAInitializerSubprocessor (data_list).run()

nn.initializers = initializers
